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On the expectation of the product of four matrix-valued Gaussian random variables

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TLDR
In this paper, the expectation of the product of four scalar real Gaussian random variables is generalized to matrix-valued (real or complex) Gaussian Random Variables, and a simple derivation of the covariance matrix of instrumental variable estimates of parameters in multivariable regression models is presented.
Abstract
The formula for the expectation of the product of four scalar real Gaussian random variables is generalized to matrix-valued (real or complex) Gaussian random variables. As an application of the extended formula, a simple derivation is presented of the covariance matrix of instrumental variable estimates of parameters in multivariable regression models. >

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References
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Journal Article

Spectral Analysis and Time Series

TL;DR: In this article, the authors introduce the concept of Stationary Random Processes and Spectral Analysis in the Time Domain and Frequency Domain, and present an analysis of Processes with Mixed Spectra.
Journal ArticleDOI

Kronecker products and matrix calculus in system theory

TL;DR: In this article, a review of the algebras related to Kronecker products is presented, which have several applications in system theory including the analysis of stochastic steady state.
Book

Instrumental Variable Methods for System Identification

TL;DR: In this article, a tutorial overview of instrumental variable methods is given, and an analysis including consistency and asymptotic distribution of the parameter estimates is included, along with a comparison with the least-squares method.
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